1. Field of the Invention
The present invention relates to the field of customer relationship management and more particularly to automated inquiry resolution for customer relationship management systems.
2. Description of the Related Art
The corporate enterprise faces a difficult challenge when attempting to simultaneously improve the quality of customer service while reducing service costs. More products, growing product complexity, third party original equipment manufacturer components, and rapid change substantially increase the amount of information required to answer customer questions and troubleshoot problems. Paradoxically, this information overload has produced an information famine in which the growth of information availability increases the difficulty of finding relevant information—particularly in an online, automated computing environment.
For the corporate enterprise to improve self-service adoption rates, increase call center efficiency and improve response accuracy, solutions are required that assist each of agents, customers, partners and suppliers in finding answers to questions more efficiently. As a result, effective solutions to information search and retrieval have become critical to inquiry resolution. One popular approach includes deploying a search engine that allows users to sift through many information sources. Typically, search engines offer any or a combination of a keyword, simple text and natural language query interface.
While the utilization of a search engine for self-service information retrieval for inquiry resolution has become commonly understood, this approach has demonstrated significant limitations. In particular, the search engine is best suited for use by expert users who are familiar with the content and terminology being searched and who know which search words will most quickly yield a correct answer. However, users without domain expertise cannot easily apply the precision and relevance required for efficient retrieval. Most will recall the experience of entering a few keywords into a search engine only to receive a resulting set of hits numbering in the thousands.
To address the limitations of the basic search engine for information retrieval, the corporate enterprise has turned to the knowledge management (KM) system to better manage and share information. The KM system has been defined as an “IT (Information Technology)-based system developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application.” The KM system intends to enable users to access to knowledge of facts, sources of information, and solutions of an organization in the course of inquiry resolution.
The modern KM system often takes the form of a document based system utilizing technologies that permit the creation, management and sharing of formatted documents. Advanced forms of the KM system include ontology based systems incorporating terminologies used to summarize a document, and artificial intelligence (AI) technologies utilizing a customized representation scheme to represent a problem domain. Generally, in a modern KM system, for inquiry resolution one or more answering servers process answer client requests for solutions statically with returned content, or actively with the conduct of a transaction.
The modern KM system provides a knowledgebase of articles answering questions posed by inquiring users. The inquiring users generally not only include customers, but also include customer service representatives seeking answers to customer questions. Inquiring users arrive at the desired article either by direct search engine query, through case based reasoning, or through AI based expert modeling in which a sub-set of selected articles are presented by reference to the inquiring user as a best guess of the desired articles.
The latter mechanism can be quite complex, however, in that in many KM system implementations an intensive manual process can be undertaken at great expense to provide the data necessary to enable the AI mechanism. In particular, the manual process often involves the collection of the statistical preferences of domain experts to produce a set of metrics ranking each article relative to a posed question. Consequently, the highest ranking articles are presented in a list to an inquiring user in response to the posed question. Due to the cost of enabling the AI mechanism, the AI mechanism has been omitted from many a KM system.